Laser Scanning Microscopy with SiPM Dark Count Correction
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Solution Overview
Problem
The use of Silicon Photomultiplier (SiPM) in laser scanning microscopes generates dark count noise, which is randomly generated and difficult to distinguish from signal photons, leading to erroneous photon counting.
Innovation Solution
A laser scanning microscope with a control device that executes image processing to remove dark count noise based on the appearance frequency of dark count noise in the SiPM, using statistical information to accurately estimate and subtract noise amounts and positions from the scanned image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If SiPM is used as a detection element to quantitatively measure photon numbers, then measurement precision is improved, but dark count noise is generated which reduces reliability
Solution Approach 1:
The system performs preliminary measurement of dark count noise characteristics before actual imaging. The processor measures the dark count noise amount and its standard deviation in advance, then uses these pre-measured values to correct the luminance values during subsequent imaging operations, separating the dark count correction step from the main imaging process.
Solution Approach 2:
The system implements feedback by using the measured dark count noise characteristics to continuously correct luminance measurements. The processor calculates corrected luminance values by subtracting the dark count noise amount from measured luminance values, and uses the standard deviation to determine confidence levels, creating a closed-loop correction mechanism.
2Reliability
If dark count noise removal processing is applied to scanned images, then reliability of photon counting is improved, but complexity of image processing increases
Solution Approach 1:
The system performs preliminary measurement of dark count noise characteristics before actual imaging. The processor measures the dark count noise amount and its standard deviation in advance, then uses these pre-measured values to correct the luminance values during subsequent imaging operations, separating the dark count correction step from the main imaging process.
Solution Approach 2:
The system replaces complex mechanical or hardware-based noise filtering with computational processing. Instead of using physical filters or complex optical systems to reduce dark count noise, the patent uses software-based algorithms that measure and subtract dark count statistics from the luminance data, achieving noise removal through information processing rather than physical means.
3Measurement precision
If dark count noise is suppressed using statistical information, then measurement precision is improved, but loss of information may occur due to noise estimation errors
Solution Approach 1:
The system applies partial correction by using the standard deviation of dark count noise to determine the confidence level of correction. When the standard deviation is large, the system reduces the correction amount or flags the measurement as unreliable, avoiding over-correction that would distort the original image characteristics. This selective correction approach preserves information while improving accuracy where confidence is high.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method effectively suppresses dark count noise, allowing for accurate photon counting without losing image characteristics, ensuring precise quantification of photon numbers.
Implementation Method 1
A luminance value of an image acquired using the SiPM is a value obtained by multiplying the number of photons incident on the SiPM by a certain coefficient
Data Source
AI summary
A laser scanning microscope includes a scanner that scans a sample with laser light; a detector having a silicon photomultiplier (SiPM); and a processor that executes image processing of removing dark count noise based on an appearance frequency of the dark count noise in the SiPM on a scanned image.